FM-ABS

This repository will hold the PyTorch implementation of the MICCAI'24 paper FM-ABS: Promptable Foundation Model Drives Active Barely Supervised Learning for 3D Medical Image Segmentation and the journal extension Journal.

[Note] Under construction. The entire project will be released upon the journal extension acceptance. The repository will be moved to New Repo soon.

Introduction

Abstract

Placeholder

🔨 Requirements

Check requirements.txt.

• Pytorch version >=0.4.1.
• Python == 3.6

💻 Usage

1. Clone the repo:

cd ./FM-ABS

2. Data Preparation Refer to ./data for details

3. Train

cd ./code
python train_FMABS_{}_3D.py --labeled_num {} --gpu 0

4. Test

cd ./code
python test_3D.py

📚 Citation

If you find this paper useful, please cite as:

@article{xu2024FMABS,
  title={FM-ABS: Promptable Foundation Model Drives Active Barely Supervised Learning for 3D Medical Image Segmentation},
  author={Xu, Zhe and Chen, Cheng and Lu, Donghuan and Sun, Jinghan and Wei, Dong and Zheng, Yefeng and Li, Quanzheng and Tong, Raymond Kai-yu},
  journal={Medical Image Computing and Computer Assisted Intervention (MICCAI)},
  year={2024}
}